Title: Automatic 2D Hand Tracking in Video Sequences
Author: Quan Yuan , Stan Sclaroff and Vassilis Athitsos
Date: November 2, 2004
Abstract:
In gesture and sign language video sequences, hand motion tends to be
rapid, and hands frequently appear in front of each other or in front
of the face. Thus, hand location is often ambiguous, and naive
color-based hand tracking is insufficient. To improve tracking
accuracy, some methods employ a prediction-update framework, but such
methods require careful initialization of model parameters, and tend
to drift and lose track in extended sequences. In this paper, a
temporal filtering framework for hand tracking is proposed that can
initialize and reset itself without human intervention. In each frame,
simple features like color and motion residue are exploited to
identify multiple candidate hand locations. The temporal filter then
uses the Viterbi algorithm to select among the candidates from frame
to frame. The resulting tracking system can automatically identify
video trajectories of unambiguous hand motion, and detect frames where
tracking becomes ambiguous because of occlusions or
overlaps. Experiments on video sequences of several hundred frames in
duration demonstrate the system's ability to track hands robustly, to
detect and handle tracking ambiguities, and to extract the
trajectories of unambiguous hand motion.